Algorithms and Metaphors for Graph Visualization
Relational data sets are often visualized with graphs: objects become the graph vertices and relations become the graph edges. Graph drawing algorithms aim to present such data in an effective and aesthetically appealing way. Map representations, provide a way to visualize relational data with the help of conceptual maps as a data representation metaphor. While graphs often require considerable effort to comprehend, a map representation is more intuitive, as most people are familiar with maps and standard map interactions via zooming and panning. The graph-to-map (GMap) algorithmic framework will be discussed, including applications, as well as experimental results on the effectiveness of the approach.
BIO: Stephen Kobourov is a Professor of Computer Science at the University of Arizona. He completed BS degrees in Mathematics and Computer Science at Dartmouth College in 1995, and a PhD in Computer Science at Johns Hopkins University in 2000. He has worked as a Research Scientist at AT&T Research Labs, as Hulmboldt Fellow at the University of Tübingen in Germany, and as a Distinguished Fulbright Chair at Charles University in Prague.